Full research paper
Physical activity types and atrial fibrillation risk in the middle-aged and elderly: The Rotterdam Study
European Journal of Preventive Cardiology 0(00) 1–8 ! The European Society of Cardiology 2018 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/2047487318780031 journals.sagepub.com/home/ejpc
Marijn Albrecht1,*, Chantal M Koolhaas1,*, Josje D Schoufour1, Frank JA van Rooij1, M Kavousi1, M Arfan Ikram1,2,3 and Oscar H Franco1
Abstract Background: The association between physical activity and atrial fibrillation remains controversial. Physical activity has been associated with a higher and lower atrial fibrillation risk. These inconsistent results might be related to the type of physical activity. We aimed to investigate the association of total and types of physical activity, including walking, cycling, domestic work, gardening and sports, with atrial fibrillation. Design: Prospective cohort study. Methods: Our study was performed in the Rotterdam Study, a prospective population-based cohort. We included 7018 participants aged 55 years and older with information on physical activity between 1997–2001. Cox proportional hazards models were used to examine the association of physical activity with atrial fibrillation risk. Models were adjusted for biological and behavioural risk factors and the remaining physical activity types. Physical activity was categorised in tertiles and the low group was used as reference. Results: During 16.8 years of follow-up (median: 12.3 years, interquartile range: 8.7–15.9 years), 800 atrial fibrillation events occurred (11.4% of the study population). We observed no association between total physical activity and atrial fibrillation risk in any model. After adjustment for confounders, the hazard ratio and 95% confidence interval for the high physical activity category compared to the low physical activity category was: 0.71 (0.80–1.14) for total physical activity. We did not observe a significant association between any of the physical activity types with atrial fibrillation risk. Conclusion: Our results suggest that physical activity is not associated with higher or lower risk of atrial fibrillation in older adults. Neither total physical activity nor any of the included physical activity types was associated with atrial fibrillation risk.
Keywords Atrial fibrillation, elderly, physical activity, epidemiology, Rotterdam Study Received 22 January 2018; accepted 9 May 2018
Introduction Physical activity (PA) has been extensively proven to reduce the risk of cardiovascular disease (CVD) and all-cause mortality.1,2 However, it remains unclear whether all cardiovascular conditions, including atrial fibrillation (AF), the most common chronic cardiac arrhythmia with significant morbidity and mortality,3 may benefit from PA. Prevalent and incident AF is associated with higher risk of myocardial infarction, heart failure and all-cause mortality.4,5 Therefore, to reduce the overall burden associated with CVDs
1 Department of Epidemiology, Erasmus MC – University Medical Center Rotterdam, The Netherlands 2 Department of Neurology, Erasmus MC – University Medical Center Rotterdam, The Netherlands 3 Department of Radiology, Erasmus MC – University Medical Center Rotterdam, The Netherlands
*These authors contributed equally to this work. Corresponding author: Chantal M Koolhaas, Department of Epidemiology – Erasmus University Medical Center, PO Box 2040, 3000 CA Rotterdam, The Netherlands. Email:
[email protected]
2 in the general population, knowing more about potential factors associated with AF risk is important. However, the relation between PA an AF remains controversial.6–8 Meta-analyses of mostly prospective cohort studies with ages of participants ranging from 40 up to 75 years found no significant association between leisure time PA and AF risk in pooled analyses.6,7 However, it has been hypothesised that the relation between PA and AF is U-shaped, with lower risk when exercising at moderate intensity or duration, but not when exercising vigorously.9–11 A recent review indicated that especially strenuous exercise is related to the development of AF in well-trained individuals.12 As intensity is related to the type of PA, this implies that the association between PA and AF risk might be related to the type of PA in which adults engage in. Two studies have found that walking and cycling were inversely related to AF risk.9,13 In addition to these activities, older people engage in a number of other PA types, including gardening, domestic work or sports in general. These different PA types vary in intensity, frequency and duration, and might be differently associated with AF risk. For older people unable to engage in certain leisure-time activities, the health effects of other PA types might be informative and crucial in lowering their AF risk. Since overall PA levels tend to decrease with age, this is especially important.14 Therefore, we aimed to examine the association between total PA and AF incidence in a population of older adults, aged 55 years and over. Furthermore, we assessed the independent association of different types of PA, including walking, gardening, domestic work, sports and cycling, with AF incidence.
Methods Study population This study was embedded within the Rotterdam Study (RS), a prospective population-based cohort study among subjects aged 55 years or older in the municipality of Rotterdam, The Netherlands. Between 1990–1993, the baseline examination of the original cohort was performed (RS-I). The RS was extended in 2000–2001 with 3011 participants who had either become 55 years old or had moved into the study district (RS-II). For this study, we used data from the participants attending the third examination of the original cohort (RS-I-3, between 1997–1999; n ¼ 4797) and the participants attending the first examination of the extended cohort (RS-II-1, between 2000–2001; n ¼ 3011).15 Altogether, 7310 participants completed PA data collection. Subjects with prevalent AF were excluded (n ¼ 205) (see Supplementary Material Figure 1). Following this, 54 subjects were excluded
European Journal of Preventive Cardiology 0(00) due to not providing, or having withdrawn, informed consent for collection of follow-up data. Thirty-three cases were removed because of unreliable PA values or missing follow-up data. A total of 7018 subjects were included in the analyses. Baseline information was collected by trained research assistants who interviewed the participants at home. All subjects gave written consent, and the study protocol was approved by the medical ethics committee according to the Wet Bevolkingsonderzoek ERGO (Population Study Act Rotterdam Study), executed by the Ministry of Health, Welfare and Sport of The Netherlands. Detailed information on the design of the Rotterdam Study can be found elsewhere.15 Covariates were assessed when participants visited the study centre or were collected through home interviews. Information regarding the measurement of covariates is provided as online Supplementary Material.
Physical activity assessment PA levels were assessed with an adapted version of the Zutphen Physical Activity Questionnaire.16 The original questionnaire has been validated with a test-retest reliability of 0.93 and a correlation with doubly labelled water of 0.61.17 The questionnaire contains questions regarding the average weekly duration in walking, cycling, sports, gardening and hobbies over the past year. Questions on domestic work were added to obtain a more reliable estimate of the PA level in this age group. Detailed information on the collection of PA can be found elsewhere.18 We used the metabolic equivalent of task (MET) to quantify the intensity of an activity according to the 2011 updated version of the Compendium of Physical Activities.19 Sports that were mentioned in the questionnaire that were not in this compendium were not used in the analyses (n ¼ 33). Finally, we calculated METhoursweek-1 in total PA (i.e. the sum of cycling, walking, sports, domestic work and gardening) and in every type of PA (cycling, walking, sports, domestic work, gardening).
Clinical outcome The main outcome measure under study was AF. Data on clinical outcomes were collected through an automated follow-up system involving digital linkage of the study database to medical records maintained by general practitioners working in the research area. Trained research assistants collected notes, outpatient clinic reports, hospital discharge letters and electrocardiograms (ECGs). AF was coded as an event when it had been diagnosed with a 12-lead ECG. Research physicians independently adjudicated all data on
Albrecht et al. potential events. Medical specialists reviewed potential cases as a final decision. Follow-up was complete until 1 January 2014.
Statistical analysis Due to their non-normal distribution, all five PA types and total PA were categorised into tertiles. Total PA, walking and domestic work were divided into three categories of equal size by the 33rd and 66th percentiles of METhweek1. Since a large proportion of the participants did not participate in sports, gardening and cycling, the bottom category for these types was no participation and the remaining two categories were created by using the median.18 We assessed the association of total PA and all types of PA with incident AF with Cox proportional hazards, after confirming that the assumption for proportional hazards was met. The underlying timescale in these models was follow-up time, defined as the time between PA assessment and the first fatal or nonfatal AF event, death, or censoring at 1 January 2014. Additionally, we applied natural cubic splines to test for non-linearity of the survival models,20 but we found no evidence for a nonlinear association between PA and AF risk. To minimise confounding, covariates were added separately in different models. Model 1 was adjusted for age and sex. Model 2 was the model additionally adjusted for behavioural risk factors, including smoking, prevalent CVD, alcohol consumption, diet quality and education. For the PA types, model 2 was also adjusted for the METhweek1 in all other PA types. The decision to include confounders in the multivariable regression models was based on previous literature or >10% change of the effect estimate in the crude model.6,7 PA variables were entered as categorical variables (tertiles) in the separate models. In sensitivity analyses, to examine the effect of biological risk factors, we repeated our analyses in a model additionally adjusted for body mass index (BMI), total and high-density lipoprotein (HDL)-cholesterol, diabetes, lipid-reducing agents, systolic and diastolic blood pressure, anti-thrombotic agents and angiotensin-converting enzyme (ACE)-inhibitor use. We also performed stratified analyses by sex and age (below 65 years and 65 years and above). Furthermore, to see whether our results would be driven by CVD, we performed an additional analysis by excluding participants with prevalent CVD (n in analysis ¼ 5997), and we performed an analysis excluding participants who developed coronary heart disease in the followup period (n in analysis ¼ 5887). Since we did not obtain occupational PA data, we analysed our data in non-workers (n in analysis ¼ 6197). Finally, because of high risk of mortality in this population, we evaluated
3 the association in a competing risk analysis, using the method proposed by Fine and Gray.21 Our data contained missing values for diet (28.7%), systolic and diastolic blood pressure (10.2%), BMI (10.6%), total cholesterol (13.2%) and HDL-cholesterol (14.2%). Other covariates had
